Modelling patient flows and resource provision in health systems

Patient flow models may be used for planning health services for both acute and chronic patients. There are models which assume sub-groups of patients are homogeneous and events occur at equally spaced intervals of time. These include Markov and semi-Markov chain models, queueing models and deterministic models of the transition of patients between states. These techniques are useful for examining patient flow in large population groups where Markov assumptions, or simple extensions of these, can be made. Discrete event simulation models allow patients to have individual attributes and to interact with resource provision but they are more time consuming to test and run. They are particularly suitable for models of system of patient care where the constraints on resource availability are important. They may also be used on unconstrained population models with several thousands of patients. A significant development in simulation is the facility to model entities so that they can participate in more than one activity simultaneously and interrupt each other. The credibility of any model is dependent on reliable data which are not always readily available in the British Health Service.